MODERN BUSINESS
mostly unconnected stands of mature
trees and a vast expanse of paddock,
they were more than surprised. After
the initial shock and some resistance,
they agreed to fund the tree-planting
project.
Cognitive psychologist Gary Klein
has said that ‘insight is when you
unexpectedly come to a better
story’. These councillors had just
had an insight, one that we helped
them to have.
Back then, I was unaware of the role
stories play in the process of making
sense of the data and communicating
insights the analyst uncovers. But over
the last 15 years, my work in business
story techniques and my interest in
conveying the results of data analysis
have merged, and I now see a strong
role for story work beyond just telling
the story of the results.
What follows is a framework for how
story techniques can help the data
analysis process.
It is useful for any individual (or group)
working with data, whether you’re a
scientist, a marketer, an engineer or a
policy-maker. The challenge in each
case is similar: how do you put yourself
in the best position to make sense of a
mass of data in order to gain insights,
and then inspire people to change
based on the discoveries?
about it in a way that helps them care.
Cole Nussbaumer Knaflic’s Storytelling
with Data also points to the popularity
of the idea.
However, Nussbaumer Knaflic’s book
is really a guide to data visualisation,
with only a single chapter on
storytelling. And while Dykes laments
the missing link between the analyst
and the decision-maker, his article
doesn’t take the opportunity to
appreciate the wider role stories play
in data analysis, beyond just inspiring
the decision-maker.
Here, we will explore the three types of
story work, the role stories play before,
during and after the data analysis, and
the various story patterns that could be
employed to inspire a decision-maker
to take action.
THE THREE TYPES OF STORY WORK
In addition to storytelling, there are
at least two other ways to employ
story work. You can elicit stories to
find out what is really happening and
how people are thinking. I call this
story-listening. You can also trigger
the telling of a new story by doing
something remarkable that others will
remark on. I call this story-triggering.
All three forms of story work –
storytelling, story-listening and storytriggering – play a role in discovering
an insight and influencing a decisionmaker to act.
Let’s explore these three types of
story work from three perspectives of
data analysis: what happens before
analysis, what happens during it, and
what happens after the insight has
been discovered.
BEFORE DATA ANALYSIS
In business, data analysis serves a
purpose. The results of an analysis
are designed to inform or even inspire
decisions – we are not talking about
pure research here. And you typically
know who’s going to make these
decisions. It might be a select number
of leaders in a company, or a broader
population of people with a specific
demographic, such as overweight,
50+ men prone to heart disease.
Regardless of the size and shape of
the group you plan to influence, it’s
useful to get an idea of the stories they
already tell, especially the ones they
tell themselves.
Long before Jon Snow became famous
for being the King of the North, a more
Figure 1
We are starting to see things written
about the role of stories in data
analysis. For example, Brent Dykes
over at Forbes has written a compelling
piece describing the need for data
storytelling, showing that the emphasis
today is on data manipulation and
analysis tools and skills. He predicts
there will be a shift to storytelling when
the gap widens between the analysts
who are discovering the insight and
the decision-makers who are learning
October 2016
ModernBusiness
29